WP BUDDIES TOOLS

Built for the everyday doers.

Small, focused tools for website owners, designers and developers. No visitor accounts or subscriptions. Most tools work locally; temporary screenshot sharing is an optional server-backed feature.

Twenty-two tools, one simple workspace

Compress, resize, crop and convert images; create image-only PDFs; add watermarks; generate favicons; inspect image dimensions and colours; and work with JSON, URLs, Base64, passwords, hashes, text and UUIDs. Create static QR codes or upload a screenshot for an unlisted seven-day sharing link.

Practical limits, clearly stated

Most image tools accept up to 20 files, 25 MiB per file and 100 MiB per batch. Processing is limited to 16 megapixels per image. Formats depend on browser decoding. JPG, PNG, WebP and BMP exports are included; AVIF output is offered only after an encoder support test. HEIC, TIFF, RAW and animation-preserving conversions are not included. Animated inputs become one still frame.

AI that runs on your device

Background removal uses U2-Net portable, with ONNX Runtime Web. It is a lightweight saliency model, not a guarantee of perfect masks. Complicated backgrounds, fine hair and transparency can need additional editing.

A note about the source

The website is compiled TypeScript with static HTML and CSS. The original tools and QR generator do not require WordPress, a database or Node.js on the hosting server. Screenshot sharing adds a PHP 8.2+ service with GD and Fileinfo and private disk storage. Tool analytics adds a small first-party PHP endpoint and private aggregate storage; country reporting can use a hosting/CDN country header or an IP-to-country lookup when no header is available. It uses locked flat-file metadata rather than a database. The AI model and runtime are optional downloads; AI-selected images are processed locally. Screenshot uploads are handled by the WP Buddies server, not a third-party image host. The interface font is loaded from Google Fonts, with a system-font fallback when unavailable.

Credits

U2-Net: Xuebin Qin, Zichen Zhang, Chenyang Huang, Masood Dehghan, Osmar R. Zaiane and Martin Jagersand, “U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection”, Pattern Recognition 106 (2020), 107404. Runtime: Microsoft ONNX Runtime Web. See the included third-party notices for source and licence references.